Seminar report

FROM CLOUD TO FOG AND IoT
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TOPIC: FROM CLOUD COMPUTING TO FOG COMPUTING AND INTERNET OF THINGS
(IoT)
SUBMITTED BY:
ARCHANA LISBON A.

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ABSTRACT:
Fog Computing is a paradigm that extends Cloud computing and services to the
edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application
services to end-users. In this research paper, I’m going to elaborate the motivation and
advantages of Fog computing, and analyze its applications in a series of real scenarios, such as
smart traffic lights in vehicular networks and software deﬁned networks. We discuss the state-of-
the-art of Fog computing and similar work under the same umbrella. Security and privacy issues
are further disclosed according to current Fog computing paradigm.
INTRODUCTION:
CISCO recently delivered the vision of fog computing to enable applications on
billions of connected devices, already connected in the Internet of Things (IoT), to run directly at
the network edge. Customers can develop, manage and run software applications on Cisco IOx
framework of networked devices, including hardened routers, switches and IP video cameras.
Cisco IOx brings the open source Linux and Cisco IOS network operating system together in a
single networked device (initially in routers). The open application environment encourages
more developers to bring their own applications and connectivity interfaces at the edge of the
network.
Cloud computing has become the buzz word during the recent years. But it largely
depends on servers which are available in a remote location, resulting in slow response time and
also scalability issues. Response time and scalability plays a crucial role in machine to machine
communication and services. The edge computing platform solves the problems by the simple
idea of locating small servers called edges servers in the vicinity of the users and devices and
passing to the servers some of the load of center servers and/or user’s devices.
LITERATURE SURVEY:

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1. www. ijarcsse.com (IEEE Research paper)
2. BROWN, R. and ROACH, W.T. (1976), The physics of radiation fog: II - A numerical study,
Quart. J. Roy. Meteor. Soc. 102, 335–354. BROWN, R. (1980),
3. A numerical study of radiation fog with an explicit formulation of the microphysics, Quart. J.
Roy. Meteor. Soc. 106, 781–802. BYERS, H.R., General Meteorology, Third Ed., (McGraw
Hill, New York 1959).
4. eISSN: 2319-1163 | pISSN: 2321-7308
IJRET: International Journal of Research in Engineering and Technology
There are many researches are going on the Fog Computing and the Internet of Things
(IoT). Lot many papers are published based on the Fog and IoT. For my seminar purpose I have
referred many online publishes and articles which helped me to learn and get a clear idea
regarding the concepts of Fog and IoT. Hoe the security is provided is easily understood by
reading the IEEE paper.

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WHAT IS CLOUD COMPUTNG?
Cloud computing is a delivery platform which promises a new way of accessing
and storing personal as well as business information. Cloud computing refers to the practice of
transitioning computer services such as computation or data storage to multiple redundant offsite
locations available on the Internet, which allows application software to be operated
using internet-enabled devices.
WHAT IS FOG COMPUTING?
Fog computing is a model in which data, processing and applications are
concentrated in devices at the network edge rather than existing almost entirely in the cloud.Fog
Computing is a paradigm that extends Cloud Computing and services to the edge of the network,
similar to Cloud, Fog provides data, compute, storage, and application services to end-users.
Fog computing is a paradigm which extends cloud computing paradigm to the
edge of the network. Terms Edge Computing and Fog Computing are often used
interchangeably. Similar to Cloud, Fog provides data, compute, storage, and application services
to end-users. This enables new breed of applications and services.
CHARACTERISTICS OF FOG COMPUTING :
 Proximity to end-users, its
 Dense geographical distribution
 Support for mobility.
Fog reduces service latency, and improves QoS (Quality of Service), resulting
in superior user-experience. Fog Computing supports emerging Internet of Everything (IoE)
applications that demand real-time/predictable latency (industrial automation, transportation,
networks of sensors and actuators). Fog paradigm is well positioned for real time Big Data and
real time analytics, it supports densely distributed data collection points, hence adding a fourth
axis to the often mentioned Big Data dimensions (volume, variety, and velocity).
Unlike traditional data centers, Fog devices are geographically distributed
over heterogeneous platforms, spanning multiple management domains. That means data can be
processed locally in smart devices rather than being sent to the cloud for processing.

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Fog Computing Services cover:
 Applications that require very low and predictable latency.
 Geographically distributed applications
 Fast mobile applications
 Large-scale distributed control systems
WHY DO WE NEED FOG COMPUTING?
In the past few years, Cloud computing has provided many opportunities for
enterprises by offering their customers a range of computing services. Current “pay-as-you-go”
Cloud computing model becomes an efficient alternative to owning and managing private data
centers for customers facing Web applications and batch processing Cloud computing frees the
enterprises and their end users from the speciﬁcation of many details, such as storage resources,
computation limitation and network communication cost.
However, this bliss becomes a problem for latency-sensitive applications, which
require nodes in the vicinity to meet their delay requirements. When techniques and devices of
IoT are getting more involved in people’s life, current Cloud computing paradigm can hardly
satisfy their requirements of mobility support, location awareness and low latency.
Fog computing is proposed to address the above problem. As Fog computing is
implemented at the edge of the network, it provides low latency, location awareness, and
improves quality-of-services (QoS) for streaming and real time applications. Typical examples
include industrial automation, transportation, and networks of sensors and actuators. Moreover,
this new infrastructure supports heterogeneity as Fog devices include end-user devices, access
points, edge routers and switches. The Fog paradigm is well positioned for real time big data
analytics, supports densely distributed data collection points, and provides advantages in
entertainment, advertising, personal computing and other applications
WHAT CAN WE DO WITH FOG?

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We elaborate on the role of Fog computing in the following motivating
scenarios. The advantages of Fog computing satisfy the requirements of applications in these
scenarios.
Smart Traffic Lights and Connected Vehicles:
Video camera that senses an ambulance flashing lights can automatically
change street lights to open lanes for the vehicle to pass through traffic. Smart street lights
interact locally with sensors and detect presence of pedestrian and bikers, and measure the
distance and speed of approaching vehicles. Intelligent lighting turns on once a sensor identifies
movement and switches off as traffic passes. Neighboring smart lights serving as Fog devices
coordinate to create green traffic wave and send warning signals to approaching vehicles.
Wireless access points like Wi-Fi, 3G, road-side units and smart traffic lights are deployed along
the roads. Vehicles-to Vehicle, vehicle to access points, and access points to access points
interactions enrich the application of this scenario.
Wireless Sensor and Actuator Networks:
Traditional wireless sensor networks fall short in applications that go
beyond sensing and tracking, but require actuators to exert physical actions like opening, closing
or even carrying sensors. In this scenario, actuators serving as Fog devices can control the
measurement process itself, the stability and the oscillatory behaviours by creating a closed-loop
system. For example, in the scenario of self-maintaining trains, sensor monitoring on a train’s
ball-bearing can detect heat levels, allowing applications to send an automatic alert to the train
operator to stop the train at next station for emergency maintenance and avoid potential
derailment. In lifesaving air vents scenario, sensors on vents monitor air conditions flowing in
and out of mines and automatically change air-flow if conditions become dangerous to miners
IoT and Cyber-physical systems (CPSs):

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Fog computing based systems are becoming an important class of IoT and
CPSs. Based on the traditional information carriers including Internet and telecommunication
network, IoT is a network that can interconnect ordinary physical objects with identiﬁed address.
CPSs feature a tight combination of the system’s computational and physical elements. CPSs
also coordinate the integration of computer and information centric physical and engineered
systems.
IoT and CPSs promise to transform our world with new relationships between
computer-based control and communication systems, engineered systems and physical reality.
Fog computing in this scenario is built on the concepts of embedded systems in which software
programs and computers are embedded in devices for reasons other than computation alone.
Examples of the devices include toys, cars, medical devices and machinery. The goal is to
integrate the abstractions and precision of software and networking with the dynamics,
uncertainty and noise in the physical environment. Using the emerging knowledge, principles
and methods of CPSs, we will be able to develop new generations of intelligent medical devices
and systems, ‘smart’ highways, buildings, factories, agricultural and robotic systems.
INTERNET OF THINGS (IoT):
The Internet of Things (IoT) represents a new world of information and
communication technologies (ICTs) from anytime, anyplace connectivity for anyone. All Things
in Internet of things or IoT are uniquely addressable and are connected using standard
communication protocols. It will consist of connections that will multiply and create entirely new
dynamic network of networks. In this, objects or things are made as smart so that they will
become knowledgeable and their properties such as transformation, interactions will allow them
to actively interact in environment.
The term “Internet of Things” was coined by British entrepreneur Kevin
Ashton in 1999. Typically, IoT is expected to offer advanced connectivity of devices, systems,
and services that goes beyond machine-to-machine communications (M2M) and covers a variety
of protocols, domains, and applications. The interconnection of these embedded devices
(including smart objects), is expected to usher in automation in nearly all fields, while also
enabling advanced applications like a Smart Grid, and expanding to the areas such as Smart city.
WHY FOG FOR IOT?

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The characteristics of fog computing like mobility, proximity to end-users, low
latency, location awareness, heterogeneity, and due to its support for yielding better and more
real-time applications fog computing platform is considered as the appropriate platform for
Internet of Things applications and services which include and not restricted to connected
vehicles, smart grid and smart cities.
It is estimated that by 2020, there will be 50 billion connected devices. The data
these devices will generate is going to be really huge. The speed with which data can be
collected and processed has to definitely increase. By using the concepts of fog computing, if the
same device can be used for these kind of processing, data generated can be put to immediate use
and deliver a much better user experience. Thus fog computing is going to play a big role in
internet of things applications.
Cisco in Jan 2014 unveiled a fog computing platform for internet of things called
IOx. Cisco extended their network device software with a parallel Linux stack. This enables
device makers to create their device interfaces and create and host applications on the network
device.
SECURITY IN FOG COMPUTING:
There are various ways to use cloud services to save or store files, documents and
media in remote services that can be accessed whenever user connect to the Internet. The main
problem in cloud is to maintain security for user’s data in way that guarantees only authenticated
users and no one else gain access to that data. The issue of providing security to confidential
information is core security problem, that it does not provide level of assurance most people
desire. There are various methods to secure remote data in cloud using standard access control
and encryption methods.
It is good to say that all the standard approaches used for providing security
have been demonstrated to fail from time to time for a variety of reasons, including faulty
implementations, buggy code, insider attacks, misconfigured services, and the creative
construction of effective and sophisticated attacks not envisioned by the implementers of security
procedures. Building a secure and trustworthy cloud computing environment is not enough,
because attacks on data continue to happen, and when they do, and information gets lost, there is
no way to get it back. There is a need to get solutions to such accidents.

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The basic idea is that we can limit the damage of stolen data if we decrease the value of that
stolen data to the attacker. We can achieve this through a „preventive‟ decoy (disinformation)
attack. We can secure Cloud services by implementing given additional security features.
Decoy System:
Decoy data, such as decoy documents, honey pots and other bogus
information can be generated on demand and used for detecting unauthorized access to
information and to poison the thief’s ex-filtrated information. Serving decoys will confuse an
attacker into believing they have ex-filtrated useful information, when they have not. This
technology may be integrated with user behavior profiling technology to secure a user’s data in
the Cloud. .
Whenever abnormal and unauthorized access to a cloud service is noticed,
decoy information may be returned by the Cloud and delivered in such a way that it appear
completely normal and legitimate. The legitimate user, who is the owner of the information,
would readily identify when decoy information is being returned by the Cloud, and hence could
alter the Cloud’s responses through a variety of means, such as challenge questions, to inform
the Cloud security system that it has incorrectly detected an unauthorized access. In the case
where the access is correctly identified as an unauthorized access, the Cloud security system
would deliver unbounded amounts of bogus information to the attacker, thus securing the user’s
true data from can be implemented by given two additional security features:
1. Validating whether data access is authorized when abnormal information access is
detected
2. Confusing the attacker with bogus information that is by providing decoy documents.

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We have applied above concepts to detect unauthorized data access to data stored on a
local file system by masqueraders, i.e. attackers who view of legitimate users after stealing their
credentials. Our experimental results in a local file system setting show that combining both
techniques can yield better detection results .This results suggest that this approach may work in
a Cloud environment, to make cloud system more transparent to the user as a local file system.
Advantages of Fog computing
 Bringing data close to the user. Instead of housing information at data center sites far
from the end-point, the Fog aims to place the data close to the end-user.
 Creating dense geographical distribution. First of all, big data and analytics can be done
faster with better results. Second, administrators are able to support location-based
mobility demands and not have to traverse the entire network. Third, these edge (Fog)
systems would be created in such a way that real-time data analytics become a reality on
a truly massive scale.
 True support for mobility and the IoT. By controlling data at various edge points, Fog
computing integrates core cloud services with those of a truly distributed data center
platform. As more services are created to benefit the end-user, edge and Fog networks
will become more prevalent.
 Numerous verticals are ready to adopt. Many organizations are already adopting the
concept of the Fog. Many different types of services aim to deliver rich content to the
end-user. This spans IT shops, vendors, and entertainment companies as well.
 Seamless integration with the cloud and other services. With Fog services, we’re able to
enhance the cloud experience by isolating user data that needs to live on the edge. From
there, administrators are able to tie-in analytics, security, or other services directly into
their cloud model.

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Future of Fog Computing
As more services, data and applications are pushed to the end-user, technologists
will need to find ways to optimize the delivery process. This means bringing information closer
to the end-user, reducing latency and being prepared for the Internet of Everything. There is no
doubt that IT consumerization and BYOD won’t increase in consumption. More users are
utilizing mobility as their means to conduct business and their personal lives. Rich content and
lots of data points are pushing cloud computing platforms, literally, to the edge – where the
user’s requirements are continuing to grow.
With the increase in data and cloud services utilization, Fog Computing will
play a key role in helping reduce latency and improving the user experience. We are now truly
distributing the data plane and pushing advanced services to the edge. By doing so,
administrators are able to bring rich content to the user faster, more efficiently, and – very
importantly – more economically. This, ultimately, will mean better data access, improved
corporate analytics capabilities, and an overall improvement in the end-user computing
experience
Cisco’s Ginny Nichols coined the term fog computing. The metaphor comes
from the fact that fog is the cloud close to the ground, just as fog computing concentrates
processing at the edge of the network. According to Cisco, fog computing extends from the edge
to the cloud, in a geographically distributed and hierarchical organization.
“Fog could take a burden off the network. As 50 billion objects become
connected worldwide by 2020, it will not make sense to handle everything in the cloud.
Distributed apps and edge-computing devices need distributed resources. Fog brings
computation to the data. Low-power devices, close to the edge of the network, can deliver real-
time response”says Technical Leader Rodolfo Milito, one of Cisco’s thought leaders in fog
computing.
“The Internet of Everything is changing how we interact with the real world,”
Milito added:“Things that were totally disconnected from the Internet before, such as cars, are
now merging onto it. But as we go from one billion endpoints to one trillion endpoints
worldwide, that creates not only a real scalability problem but the challenge of dealing with
complex clusters of endpoints – what we call ‘rich systems’ – rather than dealing with individual
endpoints. Fog’s hardware infrastructure and software platform helps solve that.”

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REFERENCES:
http://www.cisco.com/web/about/ac50/ac207/crc_new/university/RFP/rfp13078.html
http://www.howtogeek.com/185876/what-is-fog-computing/
http://newsroom.cisco.com/feature-content?type=webcontent&articleId=1365576
http://a4academics.com
https://en.wikipedia.org/wiki/Cloud_computing
https://en.wikipedia.org/wiki/Fog_computing
https://en.wikipedia.org/wiki/Internet_of_Things

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